# Similarity calculation

A BERT-small model pre-trained on Czech web corpora using the RetroMAE objective, developed by Seznam.cz, suitable for various natural language processing tasks.

This is a model based on sentence-transformers that can map sentences and paragraphs to a 384-dimensional dense vector space, suitable for tasks such as clustering or semantic search.

This is a model based on sentence-transformers that can map sentences and paragraphs to a 384-dimensional dense vector space, suitable for tasks such as clustering or semantic search.

This is a sentence embedding model based on sentence-transformers that can map text to a 512-dimensional vector space, suitable for tasks such as semantic search and text similarity calculation.